The majority of our applicants will have an undergraduate degree with first class or upper second class honours (or international equivalent). Offers will typically be made at 2.1 level (upper second class) or equivalent. Students with a good lower second class degree may be considered on an individual basis. In some cases your offer may include additional conditions, such as minimum grades in specified modules, in order to ensure that you are sufficiently qualified for our MSc programmes.
Students applying to this programme should have studied a subject with a substantial mathematical component at the undergraduate level. We welcome those from a variety of relevant disciplines, including mathematics, statistics, physics, engineering, economics and computer science.
Students from outside of the UK help form a global community here at QMUL. For detailed country-specific entry requirements please visit the International section of the QMUL website. If your first language is not English, you must provide evidence of your English language proficiency. Non-native English speakers are required to have minimum of IELTS 6.5 or equivalent. Find out more about our English language entry requirements. If you have not achieved the required English language level yet, you may be eligible to take a Pre-sessional English course, or continue to take English language tests in your country to reach the level needed. Visit: www.sllf.qmul.ac.uk/language-centre/presessionals
Months of entry
Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. The goal of network science is to develop tools to analyse Big Data of interacting complex networks and to propose numerical and analytical frameworks to predict their behaviour.
Since in these decades we are witnessing an exponential growth of data concerning communication networks and global infrastructures, the financial system, on-line social networks and biological networks, Network Science stands as a new discipline to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society.
Its impact and applications outside academia pervade technological sectors, finance, marketing and IT, public health and network biology, to cite a few.
This specialist masters programme aims at providing graduate students and professionals with a rigorous training in the underlying mathematical concepts, the analysis and modelling of complex networks and networked systems, complemented with training in computing, numerical simulations and massive data analysis. It is aimed towards students with a mathematical background who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models.
Why study your MSc Network Science at Queen Mary University of London?
- Training in the most recent advances of Network Science
- Numerical simulations and analysis of Big Data
- Interactions with leading experts of Network Science
- Prepares for employment in Data Science, consulting finance, software and for research in Network Science
Information for international students
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Fees and funding
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Qualification and course duration
Course contact details
- School of Mathematical Sciences
- +44 (0)20 7882 5468